{{Bringing AI straight into your existing systems}}
We integrate AI capabilities straight into your existing applications and processes. Your teams benefit from AI exactly where they already work every day.
AI right inside your applications
We integrate AI capabilities where your teams work every day, so value arises {{right in the flow of work}}, without introducing new tools.
Application analysis
We identify where AI creates real value in your existing applications.
Use case mapping, process analysis, feasibility, data availability, prioritisation, ROI framing
Model connection
We connect suitable language models securely to your systems and interfaces.
Azure OpenAI, Anthropic, REST APIs, SDKs, prompt templates, streaming
Knowledge grounding
AI reaches your own knowledge and delivers answers you can back with sources.
RAG, vector databases, embeddings, grounding, chunking, access filters, source citations
Process integration
AI capabilities run inside existing processes, with no context switch for users.
Webhooks, event triggers, Microsoft 365, Teams, Power Automate, connectors
Security & governance
Access, data and model usage stay controlled and traceable.
Roles, permissions, data classification, prompt filters, audit logs, EU region
Operation & monitoring
We watch quality, cost and availability of the AI capabilities in daily operation.
Observability, token metrics, latency monitoring, evaluations, fallback strategies, cost control
AI integration in five steps
Analysis
We identify where AI creates real value.
Analysis
We analyse applications and processes and assess use cases by feasibility, data availability and benefit. Together we prioritise the cases with the best ratio of impact to effort.
You receive a solid basis for deciding which integration is built first. The prioritised use case goes straight into the technical connection.
Connection
We connect language models securely to your systems.
Connection
We connect suitable language models to your systems and interfaces through REST APIs and SDKs, for instance Azure OpenAI or Anthropic. Prompt templates and streaming settle how the function behaves.
The AI capability is technically available and embedded in your interface. On this basis it gains access to your knowledge in the next step.
Knowledge grounding
AI reaches your own knowledge with sources you can check.
Knowledge grounding
We connect the AI to your approved sources through RAG and use embeddings, vector search and chunking. Access filters and source citations deliver answers that are verifiable and respect permissions.
Answers rest on your own content and stay open to checking. The solid knowledge base is then embedded in your real processes.
Process integration
AI capabilities run inside processes without breaks.
Process integration
We embed the AI capabilities straight into existing processes through webhooks, event triggers and connectors, for instance in Microsoft 365, Teams and Power Automate. The AI works in the context users know.
Teams use the AI exactly where they work every day, with no tool switching. The productive process is then safeguarded and monitored.
Operation
We secure and watch the AI capabilities continuously.
Operation
We govern access, data classification and prompt filters, log through audit trails and run in the EU region. Observability, token metrics and fallback strategies watch quality, cost and availability.
You receive a controlled, maintainable solution that delivers dependable value day to day. From the operational data the integration grows where the benefit is confirmed.
Why {{thinformatics}}
AI where work happens
Teams benefit right inside the applications they know.
No system switching
AI comes into existing processes instead of replacing them.
Securely connected
Models are tied to your data over secure APIs.
The fitting model
We choose the model by task, cost and data protection.
Run compliantly
Guardrails, data protection and the EU AI Act are accounted for.
Measurable benefit
The value becomes visible and the function improves.
FAQ
Answers to the questions we are asked most often about integrating AI into existing applications.
Bring AI into your systems
We talk about entry points, models and embedding AI securely into your applications.
